Pattern recognition systems employing artificial neural networks are well known in the art. The term pattern is used herein in its broadest sense to include groups of signals which can be assigned meaningful classifications, which may or may not have spatial significance.
Artificial neural networks include a matrix of interconnected processing units which include a plurality of inputs. The network is trained by use of training pattern signals, which training includes the adjustment of weights at inputs to the processing units to obtain desired outputs from the network. In addition to weighting means, processing units generally include means for summing the weighted inputs, and means for processing the weighted sum. The output from the processing units often comprises a binary signal of 0 or 1.